The Space Technology 7 Disturbance Reduction System (ST7-DRS) is a NASA technology demonstration payload that operated from January 2016 through July of 2017 on the European Space Agency's LISA Pathfinder spacecraft. The joint goal of the NASA and ESA missions was to validate key technologies for a future space-based gravitational wave observatory targeting the source-rich milliHertz band. The two primary components of ST7-DRS are a micropropulsion system based on colloidal micro-Newton thrusters (CMNTs) and a control system that simultaneously controls the attitude and position of the spacecraft and the two free-flying test masses (TMs). This paper presents our main experimental results and summarizes the overall the performance of the CMNTs and control laws. We find that the CMNT performance to be consistent with pre-flight predictions, with a measured system thrust noise on the order of 100 nN/ √ Hz in the 1 mHz ≤ f ≤ 30 mHz band. The control system maintained the TM-spacecraft separation with an RMS error of less than 2 nm and a noise spectral density of less than 3 nm/ √ Hz in the same band. Thruster calibration measurements yield thrust values consistent with the performance model and ground-based thrust-stand measurements, to within a few percent. We also report a differential acceleration noise between the two test masses with a spectral density of roughly 3 fm/s 2 / √ Hz in the 1 mHz ≤ f ≤ 30 mHz band, slightly less than twice as large as the best performance reported with the baseline LISA Pathfinder configuration and below the current requirements for the Laser Interferometer Space Antenna (LISA) mission.

By listening to gravity in the low frequency band, between 0.1 mHz and 1 Hz, the future spacebased gravitational-wave observatory LISA will be able to detect tens of thousands of astrophysical sources from cosmic dawn to the present. The detection and characterization of all resolvable sources is a challenge in itself, but LISA data analysis will be further complicated by interruptions occurring in the interferometric measurements. These interruptions will be due to various causes occurring at various rates, such as laser frequency switches, high-gain antenna re-pointing, orbit corrections, or even unplanned random events. Extracting long-lasting gravitational-wave signals from gapped data raises problems such as noise leakage and increased computational complexity. We address these issues by using Bayesian data augmentation, a method that reintroduces the missing data as auxiliary variables in the sampling of the posterior distribution of astrophysical parameters. This provides a statistically consistent way to handle gaps while improving the sampling efficiency and mitigating leakage effects. We apply the method to the estimation of galactic binaries parameters with different gap patterns, and we compare the results to the case of complete data.

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Harnessing the sheer discovery potential of GW Astronomy will require bold, deliberate, and sustained efforts to train and develop the requisite workforce. The next decade requires a strategic plan to build -from the ground up -a robust, open, and well-connected GW Astronomy community with deep participation from traditional astronomers, physicists, data scientists, and instrumentalists. This basic infrastructure is sorely needed as an enabling foundation for research. We outline a set of recommendations for funding agencies, universities, and professional societies to help build a thriving, diverse, and inclusive new field.